To meet the increasing demands in health care it has become important to analyze samples of red blood cells efficiently and accurately. There exists graphical user interfaces for the analysis of images depicting samples of red blood cells.
For example, there are graphical user interfaces which show an image of a red blood cell sample on a screen. A user may then by visual inspection scan over the image in order to analyze the sample. Such graphical user interfaces give a good spatial overview of the red blood cells in the sample. However, it is difficult to analyze the individual red blood cells with respect to different properties of red blood cells, such as color, size, shape, and inclusions.
Other graphical user interfaces take another approach and extract the red blood cells from the image and present the extracted red blood cells side by side on a screen. Moreover, the extracted red blood cells may be sorted based on different properties. In this way it is possible to analyze the individual red blood cells with respect to different properties of the red blood cells in the sample. However, since the red blood cells are extracted from the image the spatial context of the red blood cells in the sample is lost. There is thus room for improvements.